2020
DOI: 10.1155/2020/1468109
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Constrained Uncertain System Stabilization with Enlargement of Invariant Sets

Abstract: An enhanced method able to perform accurate stability of constrained uncertain systems is presented. The main objective of this method is to compute a sequence of feedback control laws which stabilizes the closed-loop system. The proposed approach is based on robust model predictive control (RMPC) and enhanced maximized sets algorithm (EMSA), which are applied to improve the performance of the closed-loop system and achieve less conservative results. In fact, the proposed approach is split into two parts. The … Show more

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Cited by 2 publications
(1 citation statement)
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“…Wan and Kothare (2003b) have proposed another efficient RMPC algorithm with a time varying terminal constraint set that not only enlarges the stability region but also reduces on-line computation. Hamdi et al (2020) introduced a combination of RMPC method and maximized invariant sets procedure based on a semidefinite programming problem that could enhance the stability region. An off-line RMPC algorithm based on polyhedral invariant set (instead of ellipsoidal invariant set) was developed by Bumroongsri and Kheawhom (2012) that yields a substantial expansion of the stabilizable region.…”
Section: Introductionmentioning
confidence: 99%
“…Wan and Kothare (2003b) have proposed another efficient RMPC algorithm with a time varying terminal constraint set that not only enlarges the stability region but also reduces on-line computation. Hamdi et al (2020) introduced a combination of RMPC method and maximized invariant sets procedure based on a semidefinite programming problem that could enhance the stability region. An off-line RMPC algorithm based on polyhedral invariant set (instead of ellipsoidal invariant set) was developed by Bumroongsri and Kheawhom (2012) that yields a substantial expansion of the stabilizable region.…”
Section: Introductionmentioning
confidence: 99%